AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for La-related protein 7

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q4G0J3

UPID:

LARP7_HUMAN

Alternative names:

La ribonucleoprotein domain family member 7; P-TEFb-interaction protein for 7SK stability

Alternative UPACC:

Q4G0J3; B2ZHN6; Q3B7A9; Q9P1S7; Q9Y3Z8

Background:

La-related protein 7 (LARP7) is a pivotal RNA-binding protein that plays a crucial role in the regulation of transcription elongation and mRNA splicing fidelity. It specifically binds to small nuclear RNAs (snRNAs), including the 7SK snRNA, forming a core component of the 7SK ribonucleoprotein (RNP) complex. This complex acts as a negative regulator of transcription elongation by sequestering the positive transcription elongation factor b (P-TEFb), thereby preventing RNA polymerase II phosphorylation. Additionally, LARP7 promotes U6 snRNA processing, essential for accurate mRNA splicing.

Therapeutic significance:

LARP7's involvement in Alazami syndrome, characterized by primordial dwarfism, severe intellectual disability, and distinct facial features, underscores its therapeutic significance. Understanding the role of LARP7 could open doors to potential therapeutic strategies for treating Alazami syndrome and improving mRNA splicing fidelity in other genetic disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we'll be in touch with all the details you need.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
No Spam. Cancel Anytime.